Results 251 to 260 of about 872,026 (339)

Advanced Microfluidics for Single Cell‐Based Cancer Research

open access: yesAdvanced Science, EarlyView.
Cutting‐edge microfluidic platforms are transforming single‐cell cancer research. This review highlights advanced technologies, from droplet microfluidics to tumour‐chips, that enable functional and spatial single‐cell analyses. By integrating biosensing, immune components, and patient‐derived materials, these systems offer new insights into tumour ...
Adriana Carneiro   +10 more
wiley   +1 more source

The Pathogenic Roles of Local Vitamin D Metabolism Defect in Valve Inflammation and Calcification

open access: yesAdvanced Science, EarlyView.
This study identifies the valvular interstitial cell populations responsible for valvular calcification induced by hyperphosphatemia and likely aging, uncovers local vitamin D metabolism defect‐induced inflammation as a critical pathogenic factor of calcific aortic valve disease, and highlights active vitamin D and ERK inhibitor as potential preventive
Ruichen Yang   +10 more
wiley   +1 more source

Effector-Memory γδ T Lymphocytes Predict CMV Disease After the Withdrawal of Prophylaxis in Kidney Transplant Recipients. [PDF]

open access: yesTranspl Int
Abadie Y   +9 more
europepmc   +1 more source

Life Factors and Melanoma: From the Macroscopic State to the Molecular Mechanism

open access: yesAdvanced Science, EarlyView.
Melanoma, an aggressive skin cancer, arises from dynamic interactions between genetic, environmental, and lifestyle factors. This review explores how age, gender, obesity, diet, exercise, smoking, alcohol, UV exposure, circadian rhythms, and medications influence melanoma risk and progression.
Hanbin Wang   +4 more
wiley   +1 more source

Patterns of cytokine gene expression of naïve and memory T lymphocytes in vivo. [PDF]

open access: yes, 2002
Bailey, S.   +3 more
core  

Predicting Immunotherapy Outcomes in NSCLC Using RNA and Pathology from Multicenter Clinical Trials

open access: yesAdvanced Science, EarlyView.
LIRA, a machine learning‐based model, is developed using transcriptomic data from 891 NSCLC patients in the OAK and POPLAR cohorts. Its predictive performance is validated in multiple external cohorts. Patients stratified by LIRA‐score exhibit distinct clinical characteristics and tumor microenvironment profiles.
Zhaojun Wang   +32 more
wiley   +1 more source

HLA-DR expression in cytotoxic T lymphocytes: a key to boost the therapeutic potential of T cell-based strategies for breast cancer. [PDF]

open access: yesFront Immunol
Salvador R   +13 more
europepmc   +1 more source

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